Onset of Mild Cognitive Impairment in Parkinson Disease

Objective: Characterize the onset and timing of cognitive decline in Parkinson disease (PD) from the first recognizable stage of cognitively symptomatic PD-mild cognitive impairment (PD-MCI) to PD dementia (PDD). Thirty-nine participants progressed from PD to PDD and 25 remained cognitively normal. Methods: Bayesian-estimated disease-state models described the onset of an individual’s cognitive decline across 12 subtests with a change point. Results: Subtests measuring working memory, visuospatial processing ability, and crystalized memory changed significantly 3 to 5 years before their first nonzero Clinical Dementia Rating and progressively worsened from PD to PD-MCI to PDD. Crystalized memory deficits were the hallmark feature of imminent conversion of cognitive status. Episodic memory tasks were not sensitive to onset of PD-MCI. For cognitively intact PD, all 12 subtests showed modest linear decline without evidence of a change point. Conclusions: Longitudinal disease-state models support a prodromal dementia stage (PD-MCI) marked by early declines in working memory and visuospatial processing beginning 5 years before clinical diagnosis of PDD. Cognitive declines in PD affect motor ability (bradykinesia), working memory, and processing speed (bradyphrenia) resulting in PD-MCI where visuospatial imagery and memory retrieval deficits manifest before eventual development of overt dementia. Tests of episodic memory may not be sufficient to detect and quantify cognitive decline in PD

Could scientists use Altmetric.com scores to predict longer term citation counts?

Altmetrics from Altmetric.com are widely used by publishers and researchers to give earlier evidence of attention than citation counts. This article assesses whether Altmetric.com scores are reliable early indicators of likely future impact and whether they may also reflect non-scholarly impacts. A preliminary factor analysis suggests that the main altmetric indicator of scholarly impact is Mendeley reader counts, with weaker news, informational and social network discussion/promotion dimensions in some fields. Based on a regression analysis of Altmetric.com data from November 2015 and Scopus citation counts from October 2017 for articles in 30 narrow fields, only Mendeley reader counts are consistent predictors of future citation impact. Most other Altmetric.com scores can help predict future impact in some fields. Overall, the results confirm that early Altmetric.com scores can predict later citation counts, although less well than journal impact factors, and the optimal strategy is to consider both Altmetric.com scores and journal impact factors. Altmetric.com scores can also reflect dimensions of non-scholarly impact in some fields

Validation of a social cohesion theoretical framework: a multiple group SEM strategy

Social cohesion dates back to the end of the nineteenth century. Back then, society experienced epochal transformations, as are also happening nowadays. Whenever there are epochal changes, a social order (cohesion) matter arises. The paper provides a conceptual scheme of social cohesion identifying its constituent dimensions subdivided by three spheres (macro, meso, micro) and two perspectives (objective and subjective). The overarching aim is to test the validity of the operationalization of the social cohesion model provided. Firstly, we conducted an exploratory factor analysis introducing an approach implemented in Mplus named exploratory structural equation modeling that shows several useful characteristics. Afterward, through a structural equation modeling approach, we performed several confirmatory factor analyses adopting a multiple group SEM strategy in order to cross-validate the social cohesion model

A competence-based and multidimensional operationalization and measurement of employability

Employability is a critical requirement for enabling both sustained competitive advantage at the firm level and career success at the individual level. We propose a competence-based approach to employability derived from an expansion of the resource-based view of the firm. In this contribution, we present a reliable and valid instrument for measuring employability. This measure is based on a five-dimensional conceptualization of employability, in which occupational expertise is complemented with generic competences. Two sources of raters (employees and their immediate supervisors) are involved in developing and testing the measure. Since the five dimensions of employability explain a significant amount of variance in both objective and subjective career success, the predictive validity of the tool is promising. This instrument facilitates further scientific HRM research and is of practical value in light of job and career assessments, recruitment, staffing, career mobility, and development practice

Structural Equations Modeling

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/144267/1/jcpy83.pd

Structural equation modeling in medical research: a primer

<p>Abstract</p> <p>Background</p> <p>Structural equation modeling (SEM) is a set of statistical techniques used to measure and analyze the relationships of observed and latent variables. Similar but more powerful than regression analyses, it examines linear causal relationships among variables, while simultaneously accounting for measurement error. The purpose of the present paper is to explicate SEM to medical and health sciences researchers and exemplify their application.</p> <p>Findings</p> <p>To facilitate its use we provide a series of steps for applying SEM to research problems. We then present three examples of how SEM has been utilized in medical and health sciences research.</p> <p>Conclusion</p> <p>When many considerations are given to research planning, SEM can provide a new perspective on analyzing data and potential for advancing research in medical and health sciences.</p

Coping and sickness absence

Objectives: The aim of this study is to examine the role of coping styles in sickness absence. In line with findings that contrast the reactive-passive focused strategies, problem-solving strategies are generally associated with positive results in terms of well-being and overall health outcomes; our hypothesis is that such strategies are positively related to a low frequency of sickness absence and with short lengths (total number of days absent) and durations (mean duration per spell). Methods: Using a prospective design, employees' (N = 3,628) responses on a self-report coping inventory are used to predict future registered sickness absence (i.e. frequency, length, duration, and median time before the onset of a new sick leave period). Results and conclusions: In accordance with our hypothesis, and after adjustment for potential confounders, employees with an active problem-solving coping strategy are less likely to drop out because of sickness absence in terms of frequency, length (longer than 14 days), and duration (more than 7 days) of sickness absence. This positive effect is observed in the case of seeking social support only for the duration of sickness absence and in the case of palliative reaction only for the length and frequency of absence. In contrast, an avoidant coping style, representing a reactive-passive strategy, increases the likelihood of frequent absences significantly, as well as the length and duration of sickness absence. Expression of emotions, representing another reactive-passive strategy, has no effect on future sickness absenteeism. The median time before the onset of a new episode of absenteeism is significantly extended for active problem-solving and reduced for avoidance and for a palliative response. The results of the present study support the notion that problem-solving coping and reactive-passive strategies are inextricably connected to frequency, duration, length and onset of sickness absence. Especially, active problem-solving decreases the chance of future sickness absence. © Springer-Verlag 2007

Multiple dimensions of health locus of control in a representative population sample: ordinal factor analysis and cross-validation of an existing three and a new four factor model

<p>Abstract</p> <p>Background</p> <p>Based on the general approach of locus of control, health locus of control (HLOC) concerns control-beliefs due to illness, sickness and health. HLOC research results provide an improved understanding of health related behaviour and patients' compliance in medical care. HLOC research distinguishes between beliefs due to Internality, Externality powerful Others (POs) and Externality Chance. However, evidences for differentiating the POs dimension were found. Previous factor analyses used selected and predominantly clinical samples, while non-clinical studies are rare. The present study is the first analysis of the HLOC structure based on a large representative general population sample providing important information for non-clinical research and public health care.</p> <p>Methods</p> <p>The standardised German questionnaire which assesses HLOC was used in a representative adult general population sample for a region in Northern Germany (N = 4,075). Data analyses used ordinal factor analyses in LISREL and Mplus. Alternative theory-driven models with one to four latent variables were compared using confirmatory factor analysis. Fit indices, chi-square difference tests, residuals and factor loadings were considered for model comparison. Exploratory factor analysis was used for further model development. Results were cross-validated splitting the total sample randomly and using the cross-validation index.</p> <p>Results</p> <p>A model with four latent variables (Internality, Formal Help, Informal Help and Chance) best represented the HLOC construct (three-dimensional model: normed chi-square = 9.55; RMSEA = 0.066; CFI = 0.931; SRMR = 0.075; four-dimensional model: normed chi-square = 8.65; RMSEA = 0.062; CFI = 0.940; SRMR = 0.071; chi-square difference test: p < 0.001). After excluding one item, the superiority of the four- over the three-dimensional HLOC construct became very obvious (three-dimensional model: normed chi-square = 7.74; RMSEA = 0.059; CFI = 0.950; SRMR = 0.079; four-dimensional model: normed chi-square = 5.75; RMSEA = 0.049; CFI = 0.965; SRMR = 0.065; chi-square difference test: p < 0.001). Results were confirmed by cross-validation. Results based on our large community sample indicated that western general populations separate health-related control-beliefs concerning formal and informal assistance.</p> <p>Conclusions</p> <p>Future non-clinical HLOC studies in western cultures should consider four dimensions of HLOC: Internality, Formal Help, Informal Help and Chance. However, the standardised German instrument needs modification. Therefore, confirmation of our results may be useful. Future research should compare HLOC structure between clinical and non-clinical samples as well as cross-culturally.</p